Zobrazeno 1 - 10
of 533
pro vyhledávání: '"Stumpf, Michael P H"'
Autor:
Öcal, Kaan, Stumpf, Michael P. H.
Cells actively regulate their size along the cell cycle to maintain volume homeostasis across generations. While various mathematical models of cell size regulation have been proposed to explain how this is achieved, relating these models to experime
Externí odkaz:
http://arxiv.org/abs/2411.08327
Autor:
Zhang, Stephen Y, Lan, Fangfei, Zhou, Youjia, Barbensi, Agnese, Stumpf, Michael P H, Wang, Bei, Needham, Tom
Interactions and relations between objects may be pairwise or higher-order in nature, and so network-valued data are ubiquitous in the real world. The "space of networks", however, has a complex structure that cannot be adequately described using con
Externí odkaz:
http://arxiv.org/abs/2409.06302
Topological data analysis is a powerful tool for describing topological signatures in real world data. An important challenge in topological data analysis is matching significant topological signals across distinct systems. In geometry and probabilit
Externí odkaz:
http://arxiv.org/abs/2403.19097
Autor:
Stumpf, Michael P. H.
Here we introduce simple structures for the analysis of complex hypergraphs, hypergraph animals. These structures are designed to describe the local node neighbourhoods of nodes in hypergraphs. We establish their relationships to lattice animals and
Externí odkaz:
http://arxiv.org/abs/2304.00841
Autor:
Barbensi, Agnese, Yoon, Iris H. R., Madsen, Christian Degnbol, Ajayi, Deborah O., Stumpf, Michael P. H., Harrington, Heather A.
Scientific data has been growing in both size and complexity across the modern physical, engineering, life and social sciences. Spatial structure, for example, is a hallmark of many of the most important real-world complex systems, but its analysis i
Externí odkaz:
http://arxiv.org/abs/2210.07545
Biology is data-rich, and it is equally rich in concepts and hypotheses. Part of trying to understand biological processes and systems is therefore to confront our ideas and hypotheses with data using statistical methods to determine the extent to wh
Externí odkaz:
http://arxiv.org/abs/2206.09516
The complexity of biological systems, and the increasingly large amount of associated experimental data, necessitates that we develop mathematical models to further our understanding of these systems. As biological systems are generally not well unde
Externí odkaz:
http://arxiv.org/abs/2111.02170
Autor:
Roesch, Elisabeth, Greener, Joe G., MacLean, Adam L., Nassar, Huda, Rackauckas, Christopher, Holy, Timothy E., Stumpf, Michael P. H.
Increasing emphasis on data and quantitative methods in the biomedical sciences is making biological research more computational. Collecting, curating, processing, and analysing large genomic and imaging data sets poses major computational challenges
Externí odkaz:
http://arxiv.org/abs/2109.09973
Innovation in synthetic biology often still depends on large-scale experimental trial-and-error, domain expertise, and ingenuity. The application of rational design engineering methods promise to make this more efficient, faster, cheaper and safer. B
Externí odkaz:
http://arxiv.org/abs/2108.07388
In many scientific and technological contexts we have only a poor understanding of the structure and details of appropriate mathematical models. We often, therefore, need to compare different models. With available data we can use formal statistical
Externí odkaz:
http://arxiv.org/abs/2012.13039